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Costable — Parametric Should-Cost Analysis MCP Server

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Costable — Parametric Should-Cost Analysis is answering right now. Last checked 9 min ago. It exposes 10 tools.

Parametric should-cost: P50/P80/P90 estimates, 801 materials, 25 countries, quote review.

Uptime history 78 days of history · worst day 93%
78 days agonow
100.0%
Uptime 24h
91 of 91 checks
10
Tools
read from the server
942 ms
Response time
average over 24h
open, no key
Access
streamable-http

Costable — Parametric Should-Cost Analysis missed one check this week

Everything else answered, so this is steady rather than shaky. We check every 15 minutes, which is how a one-off gets told apart from the start of a pattern, and how you hear about the next one within the hour instead of from your users.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 9 min ago.

run in your terminal
claude mcp add costable --transport http https://costable.ai/api/mcp
Settings → Connectors → Add custom connector, then paste this address
https://costable.ai/api/mcp
~/.codex/config.toml
[mcp_servers.costable]
url = "https://costable.ai/api/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "costable": {
      "url": "https://costable.ai/api/mcp"
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "costable": {
      "type": "http",
      "url": "https://costable.ai/api/mcp"
    }
  }
}

Available tools 10

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

calculate
calculate_cost_model
Run the Monte Carlo should-cost calculation on a cost model. Returns P50 (median), P80 and P90 cost-at-risk per unit, plus a full cost breakdown (material, labour, machine, overhead, margin).
compare
compare_manufacturing_countries
Run the cost model across multiple manufacturing countries simultaneously to identify the optimal sourcing location. Returns P50/P80/P90 per country and % delta vs baseline.
cost
create_cost_model
Create a new parametric cost model in Costable. Returns the model ID which is used by add_material_to_model, add_process_to_model, calculate_cost_model, and compare_manufacturing_countries.
estimate
estimate_part
Instantly estimate the should-cost of a manufactured part using natural language. Returns P50 (median), P80 and P90 cost-at-risk per unit based on Monte Carlo simulation of material price variance, labour rate variance and cycle time uncertainty. Use this for quick feasibility checks before building a full cost model.
labour
get_labour_rates
Get manufacturing labour rates ($/hr) for all skill levels in a given country. Data covers 16 skill levels across 25 countries (ILO/BLS/ABS sourced).
material
add_material_to_model
Add a material (BOM line) to an existing cost model. Searches the materials database by name query — no need for exact IDs.
materials
search_materials
Search the Costable materials database (37 materials with LME-sourced pricing). Returns material name, category, price per kg, density, and strength properties.
process
add_process_to_model
Add a manufacturing process step to an existing cost model. Searches the process database by name query — no need for exact IDs.
processes
search_processes
Search the Costable manufacturing process database (41 processes). Returns process name, category, machine rate ($/hr), and cycle time model.
review
review_supplier_quote
Analyse a supplier quote against Costable's should-cost benchmarks. Returns a line-by-line delta (% over/under should-cost), verdict (LOW / COMPETITIVE / HIGH / VERY HIGH), and a list of the top items to challenge in negotiation.

Endpoints

URLTransportStateLatencyChecked
https://costable.ai/api/mcp streamable-http answering 2079 ms 9 min ago

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Costable — Parametric Should-Cost Analysis — questions

Answers built from our own checks of this server.

What can Costable — Parametric Should-Cost Analysis do?
It exposes 10 tools, read directly from the server on our last check. Among them: add_material_to_model, add_process_to_model, calculate_cost_model, compare_manufacturing_countries, create_cost_model, estimate_part and 4 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
Is Costable — Parametric Should-Cost Analysis working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 942 ms. The bar chart above shows every period we have measured.
How do I connect Costable — Parametric Should-Cost Analysis?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Costable — Parametric Should-Cost Analysis need an API key?
No. Costable — Parametric Should-Cost Analysis completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 10 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Costable — Parametric Should-Cost Analysis?
It answers our handshake in 942 ms on average, which is faster than 5% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.